Alberto Schaeffer-Filho

Self-Managed Cell: A Middleware for Managing Body-Sensor Networks

Body sensor networks consisting of low-power on- body wireless sensors attached to mobile users will be used in the future to monitor the health and well being of patients in hospitals or at home. Such systems need to adapt autonomously to changes in context, user activity, device failure, and the availability or loss of services. To this end, we propose a policy- based architecture that uses the concept of a Self-Managed Cell (SMC) to integrate services, managed resources and a policy interpreter by means of an event bus. Policies permit the declarative specification of adaptation strategy for self- configuration and self-management. We present the design and implementation of the SMC and describe its potential use in a scenario for management of heart monitoring. Preliminary performance measurements are also presented and discussed.

Policy-based Management for Body-Sensor Networks

Body sensor networks e.g., for health monitoring, consist of several low-power on-body wireless sensors, higher-level devices such as PDAs and possibly actuators such as drug delivery pumps. It is important that such networks can adapt autonomously to changing conditions such as failures, changes in context e.g., user activity, or changes in the clinical condition of patients. Potential reconfiguration actions include changing the monitoring thresholds on sensors, the analysis algorithms or the configuration of the network itself. This paper presents a policy-based approach for autonomous management of body-sensor networks using the concept of a Self- Managed Cell (SMC). Ponder2 is an implementation of this approach that permits the specification and enforcement of policies that facilitate management and adaptation of the response to changing conditions. A Tiny Policy Interpreter has also been developed in order to provide programmable decision- making capability for BSN nodes.

Towards Supporting Interactions between Self-Managed Cells

Management in pervasive systems cannot rely on human intervention or centralised decision-making functions. It must be devolved, based on local decision-making and feedback control-loops embedded in autonomous components. We have previously proposed the self-managed cell (SMC) as an architectural pattern for building ubiquitous applications, where a SMC consists of hardware and software components that form an autonomous administrative domain. SMCs may be realised at different scales, from body-area networks for health monitoring, to an entire room or larger distributed settings. However, to scale to larger systems, SMCs must collaborate with each other, and federate or compose in larger SMC structures. This paper discusses requirements for interactions between SMCs and proposes key abstractions and protocols for realising peer-to-peer and composition interactions. These enable SMCs to exchange data, react to external events and exchange policies that govern their collaboration. Dynamically customisable interfaces are used for encapsulation and interaction mediation. Although the examples used here are based on healthcare scenarios, the principles and abstractions described in the paper are more generally applicable.

A framework for the design and evaluation of network resilience management

Network resilience strategies aim to maintain acceptable levels of network operation in the face of challenges, such as malicious attacks, operational overload or equipment failures. Often the nature of these challenges requires resilience strategies comprising mechanisms across multiple protocol layers and in disparate locations of the network. In this paper, we address the problem of resilience management and advocate that a new approach is needed for the design and evaluation of resilience strategies. To support the realisation of this approach we propose a framework that enables (1) the offline evaluation of resilience strategies to combat several types of challenges, (2) the generalisation of successful solutions into reusable patterns of mechanisms, and (3) the rapid deployment of appropriate patterns when challenges are observed at run-time. The evaluation platform permits the simulation of a range of challenge scenarios and the resilience strategies used to combat these challenges. Strategies that can successfully address a particular type of challenge can be promoted to become resilience patterns. Patterns can thus be used to rapidly deploy resilience configurations of mechanisms when similar challenges are detected in the live network.

An adaptive approach to network resilience: Evolving challenge detection and mitigation

It is widely agreed that computer networks need to become more resilient to a range of challenges that can seriously impact their normal operation. Challenges include malicious attacks, misconfigurations, accidental faults and operational overloads. As part of an overall strategy for network resilience, a crucial requirement is the identification of challenges in real-time, followed by the application of appropriate remedial action. In this paper, we motivate and describe a novel solution that enables the progressive multi-stage deployment of resilience strategies, based on incomplete challenge and context information. Policies are used to orchestrate the interactions between various resilience mechanisms, which incrementally identify the nature of a challenge and deploy appropriate remediation mechanisms. We demonstrate the benefits of this approach via simulation of a resource starvation attack on an Internet Service Provider infrastructure. By initially using lightweight detection and then progressively applying more heavyweight analysis, a key contribution of our work is the ability to mitigate a challenge as early as possible and rapidly detect its root cause. The approach we propose in this paper has the flexibility, reproducibility and extensibility needed to assist in the identification and remediation of various network challenges in the future.

Traffic anomaly diagnosis in Internet backbone networks

Computer networks are becoming increasingly important in supporting business and everyday activities. In particular, the Internet has become part of the critical infrastructure and has a strategic importance in our society and in the digital economy. These developments have led to a highly dynamic network utilization, where traffic fluctuations and seemingly random and anomalous traffic patterns are commonly manifested and hard to diagnose. In order to ensure the protection and resilience of such networks, it is necessary to better analyze and observe network traffic. Thus, anomaly diagnosis aims to discover and characterize critical anomalies affecting the network infrastructure, where the source of these anomalies may be deliberately malicious (e.g. attacks) or unintentional (e.g. failures, misconfigurations or legitimate but abnormal use of the network such as in flash crowds). However, although there is a multitude of algorithms and techniques looking at different elements of the analysis of network traffic anomalies, most research typically focuses on a specific aspect or methodology and there is very little regard for the overall context. This survey aims to present a comprehensive investigation of the current state of the art within the network anomaly diagnosis domain, in particular for Internet backbone networks. We decompose the overall anomaly diagnosis problem spectrum into four main dimensions, namely, processing costs, diagnosis granularity, theoretical methodologies and traffic features. Subsequently the anomaly diagnosis research area is structured further and an overview of the most relevant research is provided by individually reviewing each component of the problem spectrum and proposed solutions with a deeper focus on methodologies and features. Further, we also present and review seminal pieces of work that are considered cornerstones of the anomaly diagnosis research domain.

The Coalition Policy Management Portal for Policy Authoring, Verification, and Deployment

We are investigating computing platform-independent policy frameworks to specify, analyze, and deploy security and networking policies. The goal is to provide easy to use mechanisms for refining high-level user-specified goals into low-level controls. This scenario-based demo of a Coalition Policy Management Portal prototype uses the context of a hostage rescue situation to demonstrate usable and effective policy authoring through either natural language or structured lists that create natural language policy rules; policy visualization; analysis of policies for conflict, dominance, and coverage, and methods to resolve the issues identified; policy transformation from natural language to XML or ACPL SPL for automated enforcement, and deployment of policies onto mission equipment. The prototype builds on the SPARCLE and PONDER2 research projects.

Resilience support in software-defined networking

Software-defined networking (SDN) is an architecture for computer networking that provides a clear separation between network control functions and forwarding operations. The abstractions supported by this architecture are intended to simplify the implementation of several tasks that are critical to network operation, such as routing and network management. Computer networks have an increasingly important societal role, requiring them to be resilient to a range of challenges. Previously, research into network resilience has focused on the mitigation of several types of challenges, such as natural disasters and attacks. Capitalizing on its benefits, including increased programmability and a clearer separation of concerns, significant attention has recently focused on the development of resilience mechanisms that use software-defined networking approaches. In this article, we present a survey that provides a structured overview of the resilience support that currently exists in this important area. We categorize the most recent research on this topic with respect to a number of resilience disciplines. Additionally, we discuss the lessons learned from this investigation, highlight the main challenges faced by SDNs moving forward, and outline the research trends in terms of solutions to mitigate these challenges.

Towards SLA Policy Refinement for QoS Management in Software-Defined Networking

Software-Defined Networking (SDN) is a dynamic, adaptable, controllable and flexible network architecture. It provides an extensible platform for delivery of network services, capable of responding quickly to service requirement changes. As a result, SDN has become a suitable scenario for the application of techniques and approaches for improved infrastructure management, such as Policy-Based Management (PBM). In PBM, using techniques such as refinement, a high-level policy-e.g., specified as a Service Level Agreement (SLA) - can be translated into a set of corresponding low-level rules, enforceable in various elements of a system. However, when using SLAs, their translation to low-level policies, e.g., for controller configuration, is not straightforward. If this translation is not done properly, the controller may not be able to meet the implicit requirements of the SLA, failing to satisfy the goals described in the high-level policy. This paper proposes a novel approach towards SLA policy refinement for Quality of Service (QoS) management (based on routing) in Software-Defined Networking. It consists of an initial manual process performed by an administrator, followed by an automatic policy refinement process executed by an OpenFlow controller. As a result, our approach is capable of identifying the requirements and resources that need to be configured in accordance with SLA refinement, and can successfully configure and execute reactive dynamic actions for supporting dynamic infrastructure reconfiguration.Software-Defined Networking (SDN) is a dynamic, adaptable, controllable and flexible network architecture. It provides an extensible platform for delivery of network services, capable of responding quickly to service requirement changes. As a result, SDN has become a suitable scenario for the application of techniques and approaches for improved infrastructure management, such as Policy-Based Management (PBM). In PBM, using techniques such as refinement, a high-level policy-e.g., specified as a Service Level Agreement (SLA) - can be translated into a set of corresponding low-level rules, enforceable in various elements of a system. However, when using SLAs, their translation to low-level policies, e.g., for controller configuration, is not straightforward. If this translation is not done properly, the controller may not be able to meet the implicit requirements of the SLA, failing to satisfy the goals described in the high-level policy. This paper proposes a novel approach towards SLA policy refinement for Quality of Service (QoS) management (based on routing) in Software-Defined Networking. It consists of an initial manual process performed by an administrator, followed by an automatic policy refinement process executed by an OpenFlow controller. As a result, our approach is capable of identifying the requirements and resources that need to be configured in accordance with SLA refinement, and can successfully configure and execute reactive dynamic actions for supporting dynamic infrastructure reconfiguration.

Policy-driven network simulation: a resilience case study

Networks must be resilient to challenges such as malicious attacks or network overload and adapt their operation in an autonomous manner. Network simulations enable the testing of complex network scenarios (which would be difficult to emulate using actual hardware) in an inexpensive manner. However, it is difficult to evaluate resilience strategies that involve the interplay between a number of detection and remediation mechanisms that must be activated on demand according to events observed in the network (as opposed to hardcoded protocols). In this paper we propose the notion of a policy-based resilience simulator based on the integration of a network simulator and a policy management framework. This permits the evaluation of resilience strategies consisting of mechanisms whose behaviour can be adapted during runtime -- e.g. setting flags, dropping connections, triggering or stopping monitoring sessions, etc. We employ policies to specify the required adaptations, which are de-coupled from the hard-wired implementations of the simulated components, according to conditions observed during run-time in the simulation. We can thus observe how real policies affect the operation and the behaviour of simulated components, and then evaluate the effectiveness of resilience strategies before they are deployed in the network infrastructure.